At present,there is an increasing interest in quantitative characterization for vegetation in spatial and temporal scopes with hyperspectral data.Many spectral models and indices are being developed to improve vegetation sensitivity by minimizing the background influence.The Chlorophyll Absorption Continuum Index (CACI) is such a measure to calculate the spectral contintium on which the analyses are based on the shape and area of the troughs spanned by spectral continuum.However,different values of CACI were obtained in this method because the different positions of continuums were determined by different users.Furthermore,the sensitivity of CACI to agronomic parameters such as Green Leaf Chlorophyll Density (GLCD) has been reduced because the fixed positions of continuums are determined when the red edge shifted with the change in GLCD.A Second Chlorophyll Absorption Continuum Index (MCACI) is presented in this article.The REIP replaces the Maximum Reflectance Point (MRP) in Near-Infrared (NIR) shoulder on the continuum of CACI.The REIP is one of the main parameters that can describe the variation characteristics of vegetation.This MCACI has been proved to increase the sensitivity and predictive power of GLCD.